Title :
Kernel Sammon Map
Author :
Inaba, Fernando K. ; Salles, Evandro O T ; Rauber, Thomas W.
Author_Institution :
Dept. de Eng. Eletr., Univ. Fed. do Espirito Santo, Vitoria, Brazil
Abstract :
We extend the visualization technique of high-dimensional patterns conceived by Sammon to the case when the patterns have been previously mapped to an implicitly defined Hilbert feature space in which distances can be measured by kernels. The principal benefit of our technique is the possibility to gain insight into the distribution of the patterns, even in this generally non-accessible feature space.
Keywords :
Hilbert spaces; data visualisation; pattern recognition; principal component analysis; Hilbert feature space; high-dimensional pattern visualization technique; kernel Sammon map; nonaccessible feature space; pattern distribution; Hilbert space; Interpolation; Kernel; Stress; Training; Vectors; Visualization; Hilbert feature space; Kernel Principal Component Analysis; Kernels; Sammon map; Visualization;
Conference_Titel :
Graphics, Patterns and Images (Sibgrapi), 2011 24th SIBGRAPI Conference on
Conference_Location :
Maceio, Alagoas
Print_ISBN :
978-1-4577-1674-4
DOI :
10.1109/SIBGRAPI.2011.22
